Abstract For any genome-based research, a robust genome assembly is required. De novo assembly strategies have evolved with changes in DNA sequencing technologies and have been through at least three phases: i) short-read only, ii) short- and long-read hybrid, and iii) long-read only assemblies. Each of the phases has their own error model. We hypothesized that hidden scaffolding errors in short-read assembly and erroneous long-read contigs degrades the quality of short- and long-read hybrid assemblies. We assembled the genome of T. borchgrevinki from data generated during each of the three phases and assessed the quality problems we encountered. We developed strategies such as k-mer-assembled region replacement, parameter optimization, and long-read sampling to address the error models. We demonstrated that a k-mer based strategy improved short-read assemblies as measured by BUSCO while mate-pair libraries introduced hidden scaffolding errors and perturbed BUSCO scores. Further, we found that although hybrid assemblies can generate higher contiguity they tend to suffer from lower quality. In addition, we found long-read only assemblies can be optimized for contiguity by sub-sampling length-restricted raw reads. Our results indicate that long-read contig assembly is the current best choice and that assemblies from phase I and phase II were of lowermore »
The SAMBA tool uses long reads to improve the contiguity of genome assemblies
Third-generation sequencing technologies can generate very long reads with relatively high error rates. The lengths of the reads, which sometimes exceed one million bases, make them invaluable for resolving complex repeats that cannot be assembled using shorter reads. Many high-quality genome assemblies have already been produced, curated, and annotated using the previous generation of sequencing data, and full re-assembly of these genomes with long reads is not always practical or cost-effective. One strategy to upgrade existing assemblies is to generate additional coverage using long-read data, and add that to the previously assembled contigs. SAMBA is a tool that is designed to scaffold and gap-fill existing genome assemblies with additional long-read data, resulting in substantially greater contiguity. SAMBA is the only tool of its kind that also computes and fills in the sequence for all spanned gaps in the scaffolds, yielding much longer contigs. Here we compare SAMBA to several similar tools capable of re-scaffolding assemblies using long-read data, and we show that SAMBA yields better contiguity and introduces fewer errors than competing methods. SAMBA is open-source software that is distributed at https://github.com/alekseyzimin/masurca .
- Editors:
- Shao, Mingfu
- Award ID(s):
- 1744309
- Publication Date:
- NSF-PAR ID:
- 10383181
- Journal Name:
- PLOS Computational Biology
- Volume:
- 18
- Issue:
- 2
- Page Range or eLocation-ID:
- e1009860
- ISSN:
- 1553-7358
- Sponsoring Org:
- National Science Foundation
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Macqueen, D (Ed.)Abstract While the cost and time for assembling a genome has drastically decreased, it still remains a challenge to assemble a highly contiguous genome. These challenges are rapidly being overcome by the integration of long-read sequencing technologies. Here, we use long-read sequencing to improve the contiguity of the threespine stickleback fish (Gasterosteus aculeatus) genome, a prominent genetic model species. Using Pacific Biosciences sequencing, we assembled a highly contiguous genome of a freshwater fish from Paxton Lake. Using contigs from this genome, we were able to fill over 76.7% of the gaps in the existing reference genome assembly, improving contiguity over fivefold. Our gap filling approach was highly accurate, validated by 10X Genomics long-distance linked-reads. In addition to closing a majority of gaps, we were able to assemble segments of telomeres and centromeres throughout the genome. This highlights the power of using long sequencing reads to assemble highly repetitive and difficult to assemble regions of genomes. This latest genome build has been released through a newly designed community genome browser that aims to consolidate the growing number of genomics datasets available for the threespine stickleback fish.
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Abstract Long-read sequencing technology enables significant progress in de novo genome assembly. However, the high error rate and the wide error distribution of raw reads result in a large number of errors in the assembly. Polishing is a procedure to fix errors in the draft assembly and improve the reliability of genomic analysis. However, existing methods treat all the regions of the assembly equally while there are fundamental differences between the error distributions of these regions. How to achieve very high accuracy in genome assembly is still a challenging problem. Motivated by the uneven errors in different regions of the assembly, we propose a novel polishing workflow named BlockPolish. In this method, we divide contigs into blocks with low complexity and high complexity according to statistics of aligned nucleotide bases. Multiple sequence alignment is applied to realign raw reads in complex blocks and optimize the alignment result. Due to the different distributions of error rates in trivial and complex blocks, two multitask bidirectional Long short-term memory (LSTM) networks are proposed to predict the consensus sequences. In the whole-genome assemblies of NA12878 assembled by Wtdbg2 and Flye using Nanopore data, BlockPolish has a higher polishing accuracy than other state-of-the-arts including Racon,more »
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Due to the current limitations of sequencing technologies, de novo genome assembly is typically carried out in two stages, namely contig (sequence) assembly and scaffolding. While scaffolding is computationally easier than sequence assembly, the scaffolding problem can be challenging due to the high repetitive content of eukaryotic genomes, possible mis-joins in assembled contigs and inaccuracies in the linkage information. Genome scaffolding tools either use paired-end/mate-pair/linked/Hi-C reads or genome-wide maps (optical, physical or genetic) as linkage information. Optical maps (in particular Bionano Genomics maps) have been extensively used in many recent large-scale genome assembly projects (e.g., goat, apple, barley, maize, quinoa, sea bass, among others). However, the most commonly used scaffolding tools have a serious limitation: they can only deal with one optical map at a time, forcing users to alternate or iterate over multiple maps. In this paper, we introduce a novel scaffolding algorithm called OMGS that for the first time can take advantages of multiple optical maps. OMGS solves several optimization problems to generate scaffolds with optimal contiguity and correctness. Extensive experimental results demonstrate that our tool outperforms existing methods when multiple optical maps are available, and produces comparable scaffolds using a single optical map. OMGS can be obtainedmore »
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Abstract Genome sequences provide genomic maps with a single-base resolution for exploring genetic contents. Sequencing technologies, particularly long reads, have revolutionized genome assemblies for producing highly continuous genome sequences. However, current long-read sequencing technologies generate inaccurate reads that contain many errors. Some errors are retained in assembled sequences, which are typically not completely corrected by using either long reads or more accurate short reads. The issue commonly exists, but few tools are dedicated for computing error rates or determining error locations. In this study, we developed a novel approach, referred to as k-mer abundance difference (KAD), to compare the inferred copy number of each k-mer indicated by short reads and the observed copy number in the assembly. Simple KAD metrics enable to classify k-mers into categories that reflect the quality of the assembly. Specifically, the KAD method can be used to identify base errors and estimate the overall error rate. In addition, sequence insertion and deletion as well as sequence redundancy can also be detected. Collectively, KAD is valuable for quality evaluation of genome assemblies and, potentially, provides a diagnostic tool to aid in precise error correction. KAD software has been developed to facilitate public uses.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.1371/journal.pcbi.1009860
